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Collections including paper arxiv:1910.10683

The original T5 transformer release was done in two steps, the original T5 checkpoints and the improved T5v1

google-t5/t5-base

Translation • 0.2B • Updated Feb 14, 2024 • 1.79M • • 732
google-t5/t5-small

Translation • 0.1B • Updated Jun 30, 2023 • 3.47M • • 471
google-t5/t5-large

Translation • 0.7B • Updated Apr 6, 2023 • 378k • • 216
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 19
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 1

sentence-transformers/all-mpnet-base-v2

Sentence Similarity • 0.1B • Updated Mar 6 • 18.5M • • 1.12k
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14
google-t5/t5-base

Translation • 0.2B • Updated Feb 14, 2024 • 1.79M • • 732
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 74

Papers - Google

Lumiere: A Space-Time Diffusion Model for Video Generation

Paper • 2401.12945 • Published Jan 23, 2024 • 86
Long-form factuality in large language models

Paper • 2403.18802 • Published Mar 27, 2024 • 26
ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion

Paper • 2403.18818 • Published Mar 27, 2024 • 29
TC4D: Trajectory-Conditioned Text-to-4D Generation

Paper • 2403.17920 • Published Mar 26, 2024 • 18

LLM_architectures

Nemotron-4 15B Technical Report

Paper • 2402.16819 • Published Feb 26, 2024 • 47
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 57
RWKV: Reinventing RNNs for the Transformer Era

Paper • 2305.13048 • Published May 22, 2023 • 19
Reformer: The Efficient Transformer

Paper • 2001.04451 • Published Jan 13, 2020

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 252
A Survey on Latent Reasoning

Paper • 2507.06203 • Published 24 days ago • 85
Language Models are Few-Shot Learners

Paper • 2005.14165 • Published May 28, 2020 • 14
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14

How to Synthesize Text Data without Model Collapse?

Paper • 2412.14689 • Published Dec 19, 2024 • 53
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator

Paper • 2412.12094 • Published Dec 16, 2024 • 11
StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

Paper • 2306.07691 • Published Jun 13, 2023 • 10
iSTFTNet: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating Inverse Short-Time Fourier Transform

Paper • 2203.02395 • Published Mar 4, 2022

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 60
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report

Paper • 2405.00732 • Published Apr 29, 2024 • 122
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 43

Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping

Paper • 2402.14083 • Published Feb 21, 2024 • 49
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Paper • 2305.13245 • Published May 22, 2023 • 5
Training a T5 Using Lab-sized Resources

Paper • 2208.12097 • Published Aug 25, 2022 • 1
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints

Paper • 2212.05055 • Published Dec 9, 2022 • 5

Papers - Transfer Learning

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14

The original T5 transformer release was done in two steps, the original T5 checkpoints and the improved T5v1

google-t5/t5-base

Translation • 0.2B • Updated Feb 14, 2024 • 1.79M • • 732
google-t5/t5-small

Translation • 0.1B • Updated Jun 30, 2023 • 3.47M • • 471
google-t5/t5-large

Translation • 0.7B • Updated Apr 6, 2023 • 378k • • 216
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 252
A Survey on Latent Reasoning

Paper • 2507.06203 • Published 24 days ago • 85
Language Models are Few-Shot Learners

Paper • 2005.14165 • Published May 28, 2020 • 14
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 19
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 1

How to Synthesize Text Data without Model Collapse?

Paper • 2412.14689 • Published Dec 19, 2024 • 53
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator

Paper • 2412.12094 • Published Dec 16, 2024 • 11
StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

Paper • 2306.07691 • Published Jun 13, 2023 • 10
iSTFTNet: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating Inverse Short-Time Fourier Transform

Paper • 2203.02395 • Published Mar 4, 2022

sentence-transformers/all-mpnet-base-v2

Sentence Similarity • 0.1B • Updated Mar 6 • 18.5M • • 1.12k
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14
google-t5/t5-base

Translation • 0.2B • Updated Feb 14, 2024 • 1.79M • • 732
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 74

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 60
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report

Paper • 2405.00732 • Published Apr 29, 2024 • 122
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 43

Papers - Google

Lumiere: A Space-Time Diffusion Model for Video Generation

Paper • 2401.12945 • Published Jan 23, 2024 • 86
Long-form factuality in large language models

Paper • 2403.18802 • Published Mar 27, 2024 • 26
ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion

Paper • 2403.18818 • Published Mar 27, 2024 • 29
TC4D: Trajectory-Conditioned Text-to-4D Generation

Paper • 2403.17920 • Published Mar 26, 2024 • 18

Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping

Paper • 2402.14083 • Published Feb 21, 2024 • 49
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Paper • 2305.13245 • Published May 22, 2023 • 5
Training a T5 Using Lab-sized Resources

Paper • 2208.12097 • Published Aug 25, 2022 • 1
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints

Paper • 2212.05055 • Published Dec 9, 2022 • 5

LLM_architectures

Nemotron-4 15B Technical Report

Paper • 2402.16819 • Published Feb 26, 2024 • 47
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 57
RWKV: Reinventing RNNs for the Transformer Era

Paper • 2305.13048 • Published May 22, 2023 • 19
Reformer: The Efficient Transformer

Paper • 2001.04451 • Published Jan 13, 2020

Papers - Transfer Learning

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 14

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